With the rapid proliferation of the Internet and the World Wide Web, the amount of digital image data accessible to users has grown enormously. Image databases are becoming larger and more widespread, and there is a growing need for effective and efficient image retrieval systems. That is, systems that extract from a large collection of images ones that are "similar" to an image of interest to the user. Most existing image retrieval systems adopt the following two-step approach to search image databases: (i) indexing: for each image in the database, a feature vector capturing certain essential properties of the image is computed and stored in a featurebase, and (ii) searching: given a query image, its feature vector is computed, compared to the feature vectors in the featurebase, and images most similar to the query image are returned to the user.
For a retrieval system to be successful, the feature defined for an image should have certain desirable qualities: (i) the difference between pre-selected features of two images should be large if and only if the images are not "similar", (ii) the feature should be fast to compute, and (iii) the size of the feature should be small.
Color histograms are commonly used as feature vectors for images. Though the histogram is easy to compute and seemingly effective, it is liable to cause false positive matches, especially where databases are large, and is not robust to large appearance changes. Recently, several approaches have attempted to improve upon the histogram by incorporating spatial information with color. Many of these methods are still unable to handle large changes in appearance. For instance, the color coherence vector (CCV) method uses the image feature(s), e.g. spatial coherence of colors and pixel position, to refine the histogram. These additional features improve performance, but also require increased storage and computation time.
It remains desirable to have an efficient and accurate means of identifying and retrieving images which allows for changes in the appearance of the image content such as viewing angle and magnification.
It is an object of the present invention to provide a method and apparatus to perform efficient image comparisons.
It is another object of the present invention to provide a method and apparatus to provide a method and apparatus to perform image comparisons which allow for significant changes in the image such as viewing position, background, lighting, and focus.
It is another object of the present invention to provide a method and apparatus which enables efficient image retrieval from a database.